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Bernardo da Veiga

Personal Details

First Name:Bernardo
Middle Name:
Last Name:da Veiga
Suffix:
RePEc Short-ID:pda364
[This author has chosen not to make the email address public]
Terminal Degree:2006 Department of Economics; Business School; University of Western Australia (from RePEc Genealogy)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Michael McAleer & Bernardo da Veiga & Suhejla Hoti, 2010. "Value-at-Risk for Country Risk Ratings," Working Papers in Economics 10/29, University of Canterbury, Department of Economics and Finance.
  2. Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CARF F-Series CARF-F-186, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  3. McAleer, Michael & Shareef, Riaz & da Veiga, Bernardo, 2005. "Risk Management of Daily Tourist Tax Revenues for the Maldives," Natural Resources Management Working Papers 12128, Fondazione Eni Enrico Mattei (FEEM).
  4. Michael McAleer & Riaz Shareef & Bernardo da Veiga, 2005. "Managing Value-at-Risk in Daily Tourist Tax Revenues for the Maldives," DEA Working Papers 11, Universitat de les Illes Balears, Departament d'Economía Aplicada.

Articles

  1. Anup M. Nandialath & Bernardo da Veiga & Madan Annavarjula & Ramesh Mohan, 2014. "The effect of heteroskedasticity on factors affecting stock repurchases," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 16(2), pages 142-156.
  2. Bernardo da Veiga & Felix Chan & Michael McAleer, 2012. "It pays to violate: how effective are the Basel accord penalties in encouraging risk management?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 52(1), pages 95-116, March.
  3. McAleer, Michael & da Veiga, Bernardo & Hoti, Suhejla, 2011. "Value-at-Risk for country risk ratings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1454-1463.
  4. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(4), pages 453-475, September.
  5. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Modelling the volatility transmission and conditional correlations between A and B shares in forecasting value-at-risk," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 155-171.
  6. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
  7. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Michael McAleer & Bernardo da Veiga & Suhejla Hoti, 2010. "Value-at-Risk for Country Risk Ratings," Working Papers in Economics 10/29, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. San-Martín-Albizuri, Nerea & Rodríguez-Castellanos, Arturo, 2012. "Globalisation And The Unpredictability Of Crisis Episodes: An Empirical Analysis Of Country Risk Indexes / La Imprevisibilidad De Los Episodios De Crisis: Un Análisis Sobre Los Índices De Riesgo País ," Investigaciones Europeas de Dirección y Economía de la Empresa (IEDEE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), vol. 18(2), pages 148-155.
    2. Ledermann, Daniel & Alexander, Carol, 2012. "Further properties of random orthogonal matrix simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 56-79.
    3. Abroon Qazi & Mecit Can Emre Simsekler, 2022. "Prioritizing interdependent drivers of financial, economic, and political risks using a data-driven probabilistic approach," Risk Management, Palgrave Macmillan, vol. 24(2), pages 164-185, June.
    4. Qazi, Abroon, 2023. "Exploring Global Competitiveness Index 4.0 through the lens of country risk," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Cristina Alina Naftanaila, 2012. "Rating Based on the Country Risk," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 2(2), pages 126-135, April.
    6. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.

  2. Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CARF F-Series CARF-F-186, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Cited by:

    1. David Allen & Robert Faff, 2012. "The Global Financial Crisis: some attributes and responses," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 52(1), pages 1-7, March.

  3. McAleer, Michael & Shareef, Riaz & da Veiga, Bernardo, 2005. "Risk Management of Daily Tourist Tax Revenues for the Maldives," Natural Resources Management Working Papers 12128, Fondazione Eni Enrico Mattei (FEEM).

    Cited by:

    1. de Agostini, Paola & Lovo, Stefania & Pecci, Francesco & Perali, Carlo Federico & Baggio, Michele, 2005. "Simulating the Impact on the Local Economy of Alternative Management Scenarios for Natural Areas," Natural Resources Management Working Papers 12133, Fondazione Eni Enrico Mattei (FEEM).
    2. Guido Candela & Paolo Figini & Antonello E. Scorcu, 2005. "The Economics of Local Tourist Systems," Working Papers 2005.138, Fondazione Eni Enrico Mattei.
    3. Antonio Menezes & Ainura Uzagalieva, 2013. "The Demand of Car Rentals: a Microeconometric Approach with Count Models and Survey Data," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 5(1), pages 25-41, June.
    4. Juin‐Jen Chang & Lee‐Jung Lu & Shih‐Wen Hu, 2011. "Congestion Externalities of Tourism, Dutch Disease and Optimal Taxation: Macroeconomic Implications," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 90-108, March.
    5. Alberto Gago & Xavier Labandeira & Fidel Picos & Miguel Rodríguez, 2006. "Taxing Tourism in Spain: Results and Recommendations," DEA Working Papers 16, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    6. Jorge V Pérez-Rodríguez & María Santana-Gallego, 2020. "Modelling tourism receipts and associated risks, using long-range dependence models," Tourism Economics, , vol. 26(1), pages 70-96, February.

Articles

  1. Bernardo da Veiga & Felix Chan & Michael McAleer, 2012. "It pays to violate: how effective are the Basel accord penalties in encouraging risk management?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 52(1), pages 95-116, March.

    Cited by:

    1. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Econometric Institute Research Papers EI 2012-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Guettler, Andre & Naeem, Mahvish & Norden, Lars & Van Doornik, Bernardus, 2024. "Pre-publication revisions of bank financial statements: A novel way to monitor banks?," Journal of Financial Intermediation, Elsevier, vol. 58(C).
    3. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.

  2. McAleer, Michael & da Veiga, Bernardo & Hoti, Suhejla, 2011. "Value-at-Risk for country risk ratings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1454-1463.
    See citations under working paper version above.
  3. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(4), pages 453-475, September.

    Cited by:

    1. He, Hongbo & Chen, Shou & Yao, Shujie & Ou, Jinghua, 2014. "Financial liberalisation and international market interdependence: Evidence from China’s stock market in the post-WTO accession period," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 434-444.
    2. Abdul Hakim, 2009. "Forcasting portofolio value-at-risk for international stocks, bonds, and foreign exchange emerging market evidence," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 1(1), pages 13-26, April.
    3. Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CIRJE F-Series CIRJE-F-683, CIRJE, Faculty of Economics, University of Tokyo.
    4. Christos Agiakloglou & Charalampos Agiropoulos, 2011. "The sensitivity of Value-at-Risk estimates using Monte Carlo approach," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 61(1-2), pages 7-12, January -.
    5. Chia-Chi Sun, 2021. "An Assessment Model for Wealth Management Banks Based on the Fuzzy Evaluation Method," Mathematics, MDPI, vol. 9(19), pages 1-16, October.

  4. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Modelling the volatility transmission and conditional correlations between A and B shares in forecasting value-at-risk," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 155-171.

    Cited by:

    1. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets," KIER Working Papers 717, Kyoto University, Institute of Economic Research.
    2. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Analyzing and Forecasting Volatility Spillovers, Asymmetries and Hedging in Major Oil Markets," Working Papers in Economics 10/19, University of Canterbury, Department of Economics and Finance.
    3. Abdul Hakim, 2009. "Forcasting portofolio value-at-risk for international stocks, bonds, and foreign exchange emerging market evidence," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 1(1), pages 13-26, April.
    4. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Forecasting Volatility and Spillovers in Crude Oil Spot, Forward and Futures Markets," CARF F-Series CARF-F-163, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Weber, Enzo & Zhang, Yanqun, 2012. "Common influences, spillover and integration in Chinese stock markets," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 382-394.
    6. Lin, Wen-Yuan & Tsai, I-Chun, 2019. "Trader differences in Shanghai’s A-share and B-share markets: Effects on interaction with the Shanghai housing market," Journal of Asian Economics, Elsevier, vol. 64(C), pages 1-1.

  5. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.

    Cited by:

    1. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Econometric Institute Research Papers EI 2010-59, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Hammoudeh, S.M. & Malik, F. & McAleer, M.J., 2010. "Risk management of precious metals," Econometric Institute Research Papers EI 2010-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
    4. Chang, C-L. & Jiménez-Martín, J.A. & McAleer, M.J. & Pérez-Amaral, T., 2011. "Risk Management of Risk under the Basel Accord: Forecasting Value-at-Risk of VIX Futures," Econometric Institute Research Papers EI 2011-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Michael McAleer & Bernardo da Veiga & Suhejla Hoti, 2010. "Value-at-Risk for Country Risk Ratings," Working Papers in Economics 10/29, University of Canterbury, Department of Economics and Finance.
    6. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Econometric Institute Research Papers EI 2012-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez-Amaral, 2011. "International Evidence on GFC-robust Forecasts for Risk Management under the Basel Accord," Working Papers in Economics 11/05, University of Canterbury, Department of Economics and Finance.
    8. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    9. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "A Decision Rule to Minimize Daily Capital Charges in Forecasting Value-at-Risk," CARF F-Series CARF-F-159, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    10. Chang, C-L. & McAleer, M.J., 2009. "Daily Tourist Arrivals, Exchange Rates and Volatility for Korea and Taiwan," Econometric Institute Research Papers EI 2009-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    12. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
    13. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(4), pages 453-475, September.
    14. Sarafrazi, Soodabeh & Hammoudeh, Shawkat & AraújoSantos, Paulo, 2014. "Downside risk, portfolio diversification and the financial crisis in the euro-zone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 368-396.
    15. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
    16. Eraslan, Sercan & Ali, Faek Menla, 2017. "Financial crises and the dynamic linkages between stock and bond returns," Discussion Papers 17/2017, Deutsche Bundesbank.
    17. Santos, André A. P. & Nogales, Francisco J., 2009. "Comparing univariate and multivariate models to forecast portfolio value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws097222, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. McAleer, M.J., 2008. "The ten commandments for optimizing value-at-risk and daily capital charges," Econometric Institute Research Papers EI 2008-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Katerina Rigana & Ernst C. Wit & Samantha Cook, 2024. "Navigating Market Turbulence: Insights from Causal Network Contagion Value at Risk," Papers 2402.06032, arXiv.org.
    20. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-643, CIRJE, Faculty of Economics, University of Tokyo.
    21. Cathy W. S. Chen & Mike K. P. So & Edward M. H. Lin, 2009. "Volatility forecasting with double Markov switching GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 681-697.
    22. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    23. Juan-Angel Jimenez-Martin & Michael McAleer & Teodosio Pérez-Amaral, 2009. "The Ten Commandments for Managing Value-at-Risk Under the Basel II Accord," Documentos de Trabajo del ICAE 2009-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    24. Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CIRJE F-Series CIRJE-F-683, CIRJE, Faculty of Economics, University of Tokyo.
    25. Jose Angelo Divino & Michael McAleer, 2009. "Modelling and Forecasting Daily International Mass Tourism to Peru," CIRJE F-Series CIRJE-F-651, CIRJE, Faculty of Economics, University of Tokyo.
    26. Hakim, Abdul & McAleer, Michael, 2009. "Forecasting conditional correlations in stock, bond and foreign exchange markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2830-2846.
    27. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Optimal Risk Management Before, During and After the 2008-09 Financial Crisis," CARF F-Series CARF-F-171, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    28. Liu, Tengdong & Hammoudeh, Shawkat & Santos, Paulo Araújo, 2014. "Downside risk and portfolio diversification in the euro-zone equity markets with special consideration of the crisis period," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 47-68.
    29. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "What Happened to Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-636, CIRJE, Faculty of Economics, University of Tokyo.
    30. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
    31. Stavros Degiannakis & Apostolos Kiohos, 2014. "Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 216-232, March.
    32. Markus Haas & Jochen Krause & Marc S. Paolella & Sven C. Steude, 2013. "Time-Varying Mixture GARCH Models and Asymmetric Volatility," Swiss Finance Institute Research Paper Series 13-04, Swiss Finance Institute.
    33. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79850, Verein für Socialpolitik / German Economic Association.
    34. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    35. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    36. Anjum, Hassan & Malik, Farooq, 2020. "Forecasting risk in the US Dollar exchange rate under volatility shifts," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    37. Amira Akl Ahmed & Doaa Akl Ahmed, 2016. "Modelling Conditional Volatility and Downside Risk for Istanbul Stock Exchange," Working Papers 1028, Economic Research Forum, revised Jul 2016.
    38. Halbleib, Roxana & Pohlmeier, Winfried, 2012. "Improving the value at risk forecasts: Theory and evidence from the financial crisis," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1212-1228.
    39. Hood, Matthew & Malik, Farooq, 2018. "Estimating downside risk in stock returns under structural breaks," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 102-112.
    40. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
    41. Metiu, Norbert, 2012. "Sovereign risk contagion in the Eurozone," Economics Letters, Elsevier, vol. 117(1), pages 35-38.
    42. Svetlana Mira & Nicholas Taylor, 2013. "An International Perspective on Risk Management Quality," European Financial Management, European Financial Management Association, vol. 19(5), pages 935-955, November.
    43. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

  6. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.

    Cited by:

    1. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    2. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Econometric Institute Research Papers EI 2010-59, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Hammoudeh, S.M. & Malik, F. & McAleer, M.J., 2010. "Risk management of precious metals," Econometric Institute Research Papers EI 2010-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
    5. Chang, C-L. & Jiménez-Martín, J.A. & McAleer, M.J. & Pérez-Amaral, T., 2011. "Risk Management of Risk under the Basel Accord: Forecasting Value-at-Risk of VIX Futures," Econometric Institute Research Papers EI 2011-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Michael McAleer & Bernardo da Veiga & Suhejla Hoti, 2010. "Value-at-Risk for Country Risk Ratings," Working Papers in Economics 10/29, University of Canterbury, Department of Economics and Finance.
    7. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Econometric Institute Research Papers EI 2012-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez-Amaral, 2011. "International Evidence on GFC-robust Forecasts for Risk Management under the Basel Accord," Working Papers in Economics 11/05, University of Canterbury, Department of Economics and Finance.
    9. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    10. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    11. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "A Decision Rule to Minimize Daily Capital Charges in Forecasting Value-at-Risk," CARF F-Series CARF-F-159, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    12. Chang, C-L. & McAleer, M.J., 2009. "Daily Tourist Arrivals, Exchange Rates and Volatility for Korea and Taiwan," Econometric Institute Research Papers EI 2009-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    14. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    15. Santos, André A. P. & Nogales, Francisco J., 2009. "Comparing univariate and multivariate models to forecast portfolio value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws097222, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. McAleer, M.J., 2008. "The ten commandments for optimizing value-at-risk and daily capital charges," Econometric Institute Research Papers EI 2008-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Fortin, Alain-Philippe & Simonato, Jean-Guy & Dionne, Georges, 2018. "Forecasting Expected Shortfall: Should we use a Multivariate Model for Stock Market Factors?," Working Papers 18-4, HEC Montreal, Canada Research Chair in Risk Management, revised 25 Jun 2021.
    18. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    19. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-643, CIRJE, Faculty of Economics, University of Tokyo.
    20. Jochen Krause & Marc S. Paolella, 2014. "A Fast, Accurate Method for Value-at-Risk and Expected Shortfall," Econometrics, MDPI, vol. 2(2), pages 1-25, June.
    21. Strzalkowska-Kominiak, Ewa & Cao, Ricardo, 2013. "Maximum likelihood estimation for conditional distribution single-index models under censoring," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 74-98.
    22. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    23. Allen, David & Lizieri, Colin & Satchell, Stephen, 2020. "A comparison of non-Gaussian VaR estimation and portfolio construction techniques," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 356-368.
    24. Juan-Angel Jimenez-Martin & Michael McAleer & Teodosio Pérez-Amaral, 2009. "The Ten Commandments for Managing Value-at-Risk Under the Basel II Accord," Documentos de Trabajo del ICAE 2009-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CIRJE F-Series CIRJE-F-683, CIRJE, Faculty of Economics, University of Tokyo.
    26. Sander Barendse & Andrew J. Patton, 2020. "Comparing Predictive Accuracy in the Presence of a Loss Function Shape Parameter," Economics Series Working Papers 909, University of Oxford, Department of Economics.
    27. Jose Angelo Divino & Michael McAleer, 2009. "Modelling and Forecasting Daily International Mass Tourism to Peru," CIRJE F-Series CIRJE-F-651, CIRJE, Faculty of Economics, University of Tokyo.
    28. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "Optimal Risk Management Before, During and After the 2008-09 Financial Crisis," CARF F-Series CARF-F-171, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    29. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Perez-Amaral, 2009. "What Happened to Risk Management During the 2008-09 Financial Crisis?," CIRJE F-Series CIRJE-F-636, CIRJE, Faculty of Economics, University of Tokyo.
    30. Bogdan, Dima & Ştefana Maria, Dima & Roxana, Ioan, 2022. "A Value-at-Risk forecastability indicator in the framework of a Generalized Autoregressive Score with “Asymmetric Laplace Distribution”," Finance Research Letters, Elsevier, vol. 45(C).
    31. Mauro Bernardi & Leopoldo Catania, 2015. "The Model Confidence Set package for R," CEIS Research Paper 362, Tor Vergata University, CEIS, revised 17 Nov 2015.
    32. Stavros Degiannakis & Apostolos Kiohos, 2014. "Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 216-232, March.
    33. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    34. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    35. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    36. C. A. Abanto-Valle & V. H. Lachos & Dipak K. Dey, 2015. "Bayesian Estimation of a Skew-Student-t Stochastic Volatility Model," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 721-738, September.
    37. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    38. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    39. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    40. Francq, Christian & Zakoian, Jean-Michel, 2015. "Joint inference on market and estimation risks in dynamic portfolios," MPRA Paper 68100, University Library of Munich, Germany.
    41. Makushkin, Mikhail & Lapshin, Victor, 2020. "Modelling tail dependencies between Russian and foreign stock markets: Application for market risk valuation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 30-52.
    42. Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
    43. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    44. Mauro Bernardi & Leopoldo Catania & Lea Petrella, 2014. "Are news important to predict large losses?," Papers 1410.6898, arXiv.org, revised Oct 2014.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 7 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-RMG: Risk Management (5) 2005-12-09 2009-09-19 2009-11-27 2010-05-29 2010-09-18. Author is listed
  2. NEP-BAN: Banking (3) 2009-11-27 2010-05-29 2010-09-18
  3. NEP-FMK: Financial Markets (3) 2009-09-19 2009-12-11 2010-09-18
  4. NEP-REG: Regulation (3) 2009-11-27 2009-12-11 2010-09-18
  5. NEP-TUR: Tourism Economics (2) 2005-12-09 2006-04-08
  6. NEP-BEC: Business Economics (1) 2010-09-18
  7. NEP-FIN: Finance (1) 2005-12-09
  8. NEP-IFN: International Finance (1) 2010-05-29

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